Investigating Celastrol ’ s Anti-DCM Targets and Mechanisms via Network Pharmacology and Experimental Validation

Background and Purpose . DCM (diabetic cardiomyopathy), which may lead to signi ﬁ cant complications including cardiovascular lesions, arrhythmia, and even heart failure, has a beginning element now known to be myocardial energy rebuilding. There are limited research on Celastrol ’ s ability to guard against this in the United States and elsewhere. Since it has not been known, whether Celastrol could reverse the early energy remodeling process, thus, it was hypothesized that triptolide Celastrol is suitable for the reversal of early myocardial energy remodeling in DCM. And our aim is to predict the targets and underlying mechanism of Celastrol in reversing the early energy remodeling for DCM. Methods . Data from TCMSP and GEO databases were utilized to identify targets for Celastrol on DCM. The relationship between the major targets and conventional glycolipid metabolism was obtained with Spearman correlation analysis. Experiments on animals were conducted utilizing healthy control (HC), low-dose Celastrol interventions (CL), and no intervention groups (NC), all of which had 8 SD rats in each group. To study alterations in signaling molecules, RT-PCR was performed. Results . There were 76 common targets and 5 major targets for Celastrol-DCM. Celastrol have been found to regulate AGE-RAGE, TNF, MAPK, TOLL-like receptors, insulin resistance, and other signaling pathways, and they are closely linked to adipocytokines, fatty acid metabolism, glycolipid biosynthesis, and glycosylphosphati-dylinositol biosynthesis on DCM. These ﬁ ve major targets have been found to regulate these pathways. Experiments on rats indicated that P38 MAPK was considerably elevated in the cardiac tissue from rats in the CL and NC groups compared to the HC group, and the di ﬀ erence was statistically signi ﬁ cant ( P < 0 : 01 ). Signi ﬁ cant di ﬀ erences were seen between the CL and NC groups in P38 MAPK levels, with a statistical signi ﬁ cance level of less than 0.05. Conclusion . Celastrol may play a role in reversing energy remodeling, anti-in ﬂ ammation, and oxidative stress via modulating p38 protein expression in the MAPK pathway, which have been shown in the treatment of DCM.


Introduction
DCM involves a range of changes caused by diabetes mellitus (DM) to the myocardial structure and function [1]. The increase of fatty acid-oxidation and decrease of glucose oxidation in ventricular myocytes are the significant characteristics of DCM energy rebuilding. In some research, it has been shown that myocardial energy restoration is conducive to enhancing DCM development [2][3][4]. As a leading cause of diabetes-related mortality, DCM can have a substantial impact on the well-being of patients [5,6]. Cardiac remodeling and dysfunction may be alleviated by early intervention with the rebuilding of myocardial energy (changing the ratio of myocardial glucose to fatty acid metabolism) [7][8][9][10]. Besides, there are more and more studies confirming that the early intervention with DCM energy restoration plays an essential role in preventing myocardial remodeling and cardiac dysfunction [11,12]. Celastrol, which can produce various biological effects, has been reportedly applied for the prevention and treatment of tumors, lupus erythematosus, rheumatoid arthritis, etc. [13][14][15]. Additionally, Celastrol is regarded as having a massive potential to serve as a contemporary medicine for treatment by "CELL" due to its diverse effects [16]. However, there remains a lack of clarity on whether Celastrol can play a protective role in the early energy remodeling of DCM and its underlying mechanism. Besides, network pharmacology is a relatively new subject of study that links the disciplines like pharmacology, bioinformatics, and system biology. It provides an effective solution to revealing the mechanism of effect produced by those compounds used in traditional Chinese medicine. It entails an analysis as to the mechanism of medication-induced effects and the organisms in aggregate by establishing a "disease-target-drug" network. Thus, it is hypothesized that triptolide Celastrol is applicable to the reversal of early energy remodeling in DCM. This paper is purposed to predict the targets and underlying mechanism of Celastrol in reversing the early energy remodeling for DCM. So, network pharmacology concepts and methodologies were applied in this study to explore the key targets of Celastrol against DCM, as well as the pathways involved in the mechanism of action of DCM [17][18][19]. According to the relevant principles and methods of network pharmacology [17,20], we not only analyzed the main targets of Celastrol on DCM but also applied the research methods of "Li et al." to predict and analyze its enriched biological processes and signaling pathways [17]. Finally, during animal experiments, PCR technology was applied to confirm the content of specific molecular genes in individual signaling pathways ( Figure 1). 2.5. Construction of "Drug-Target-DCM" Network. Major targets of Celastrol against DCM were explored using STRING online database 11.0 (https://string-db.org), with a confidence score > 0:4 as the separating point standard. A network diagram of "drug-target-disease" interaction and PPI network was then constructed. Topological parameters in the network, such as median degree and maximum degree, were analyzed using NetworkAnalyzer in Cytoscape (version 3.7.1). Major targets were identified based on the degree. The upper limit of the range was the largest degree in the topological data, and the lower limit was twice the median value of the degree. The Cytoscape software was used for visualization of the PPI network.

GO and KEGG Functional Annotation and Analysis.
Functional annotation of major targets was carried out using "ClusterProfiler," R package, to comprehensively explore related function of these targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore the relevant functional categories. GO function analysis was mainly used to describe the function of major targets, including cell localization, molecular function, and biological process. KEGG enrichment analysis was used to explore enriched signaling pathways related to the common targets of Celastrol and DCM. GO and KEGG enrichment paths with P and q values less than 0.05 were considered as significant categories.

Correlation Analysis between Target and Metabolic
Pathway. The metabolic path level of each sample was quantified using ssGSEA. Spearman correlation analysis was carried out to determine correlation between gene expression quantity and metabolic pathway. healthy control SD rats, male, 200-230 g, were kept in rat cages with a temperature range of 18-26°C, a relative humidity range of 40-70%, a noise level of less than 85 dB, and an ammonia content of less than 20 ppm. They were given a breather every 8-12 hours. Sixteen model rats were randomly assigned to the Cel low-dose group (CL) or the control group that received no treatment (NC). High-sugar, high-fat diets were given to 8 rats from each group. Modeling had been completed on day 1, and therefore, treatment could begin on day 2. For the HC group, the regular diet was maintained, whereas the CL group received 50 μg/kg of body weight per day. After 4 weeks of high sugar and fat diet, the rats in the NC group were given a lethal injection. All animal experiments involving rats were performed following the Principles of Laboratory Animal Care (Peoples Republic of China), and the animal protocols were approved by the Ethics Committee of Shanxi Medical University (No. SYDL2019002).

Quantitative Real-Time Fluorescence PCR Assay (RT-PCR) for P38 MAPK Content.
A total of roughly 100 mg of fresh tissue was taken, frozen, and kept at -80°C. Total RNA was isolated from the obtained cardiac tissue using Trizol reagent (#15596-026, Ambion, California, USA) and kept at -80°C in the refrigerator as a backup. First-strand cDNA was synthesized from total RNA using 4× gDNA wiper mix (#R223-01, VAZYME, Nanjing, China). 5× HiScript II Select qRT SuperMix II (#R233-01, VAZYME, Nanjing, China) was used to detect amplification of specific PCR products according to the manufacturer's instructions. It was done by electrophoresis with GelRed and DNA markers in GelRed, which resulted in separation of PCR products from each other. As a control, GAPDH was employed. The manufacturer's instructions were followed for doing realtime quantitative PCR using SYBR Green Master Mix (#R223-01, VAZYME, Nanjing, China). Data were normalized based on β-actin mRNA levels. The final specific primer sequences (SANGON, Shanghai, China) are listed in Table 1 below.
2.9. Statistical Analysis. R was used to do network pharmacology data analysis (version 3.6). All statistical tests were two-sided, and P < 0:05 was deemed statistically significant in all cases. We conducted several basic tests and utilized the SPSS 26.0 statistical analysis software to analyze the data, with continuous variables reported in terms of mean ± standard deviation, while comparisons between two groups that satisfied the normality test were assessed by samples t.
For numerous comparisons between groups that passed the homogeneity test for variances, one-way ANOVA was used. LSD-t was used for two comparisons between groups that had identical variances. When the variance normality and homogeneity tests were not fulfilled, nonparametric tests were used to compare data from different groups.
The Kruskal-Wallis test may be used to compare two groups, and differences are regarded statistically significant if P < 0:05.

Drug and DCM Target Prediction.
A total of 161 targets associated with Celastrol were retrieved from the TCSMP database, the Swiss Target database, and the Batman database (Supplementary data 1). Differential genes of DCM were evaluated using the GSE4745 data set in the GEO database. The differential screening conditions were logFC > 1 and P < 0:05. A total of 59 differential genes were identified, including 35 upregulated genes and 24 downregulated genes (Supplementary Table 1). Targets related to DCM were explored using the DisGeNET database, OMIM database, and GeneCard database (relevance score > 5), and a total of 2075 targets related to DCM were retrieved (Supplementary data 2). Furthermore, the intersection of all targets was determined using a Venn diagram, and a total of 76 drug-DCM interactive targets were obtained ( Figure 2, Supplementary Table 2). Pharmacological targets and function-related PPI networks of Celastrol on DCM were constructed.

Construction of PPI Network and Screening of Key Target
Genes. A total of 76 Celastrol-DCM common targets were uploaded into the STRING database for PPI network analy-

GO Functional Enrichment
Analysis. GO enrichment analysis of major targets was carried out using the R software, and data were presented as a histogram, bubble diagram, and chordal graph (Figure 4). Color-code in the histogram indicates the significance of the P value of the corresponding gene. Deep red color represents highly enriched genes (Figure 4(a)). The abscissa of the bubble diagram represents the percentage of genes. A larger circle repre-sents a higher enrichment number, and deep red color implies that the expression level of the gene is significantly high (Figure 4(b)). GO enrichment analysis showed that five major targets are mainly involved in biological processes such as response to reactive oxygen species (ROS), peptidyl-serine phosphorylation, peptidyl-serine modification, lipopolysaccharide, molecules of bacterial origin, oxidative stress, and regulation of cell-cell adhesion, DNAbinding transcription factors, peptidyl-serine phosphorylation, and leukocyte migration (Supplementary Table 4).

KEGG Enrichment
Analysis. The five major targets were identified through KEGG pathway analysis using the R software ClusterProfiler package. Previous studies report that pathways related to energy reconstruction are associated 3.5. Visualization of Drug and DCM Targets. The network visualization "Celastrol-target-DCM" interaction diagram ( Figure 6) was generated using the Cytoscape software. The network showed that Celastrol regulates DCM by modulating five major targets, namely, VEGFA, MAPK8, IL6, CASP3, and TNF. This finding implies that Celastrol is implicated in abrogation of the pathogenesis of DCM.

Analysis of the Relationship between Targets and
Metabolic Pathways. Spearman correlation analysis showed that the five major targets had different degrees of correlation with disease energy metabolism. Specific manifestations observed were as follows: VEGFA was correlated with adipocytokines, lipid metabolism, fatty acid metabolism, glycolipid biosynthesis, glycosylphosphatidylinositol biosynthesis, and insulin signaling pathway whereas TNF was correlated with adipocytokines, lipid metabolism, and insulin signaling pathway. In addition, MAPK8 was correlated with fatty acid metabolism and glycolipid biosynthesis; IL6 was correlated with peroxidase activity whereas CASP3 was correlated with

Discussion
Diabetes mellitus has now become a severe public health concern worldwide [20], with the total cases of diabetics estimated to reach 629 million by 2045 [21]. DCM, as one of the primary complications and causes of mortality, was initially postulated in 1972 [22] and has since become a focus of clinical and fundamental research, attracting the attention of clinicians and researchers [23]. Furthermore, it has been confirmed by both clinical and experimental studies that various pathophysiological changes can result from myocardial energy remodeling, reduced sugar and lactate metabolism, and increased lipid metabolism, such as oxidative stress, apoptosis, endothelial dysfunction, increased inflammatory response, blood hypercoagulation, and myocardial fibrosis, as well as the damage caused to mitochondria, cells, and microcirculation, interstitial fibrosis, and the structural and functional changes in the myocardium. It is manifested as the catastrophic repercussions like microvascular and macrovascular cardiac issues, cardiac arrhythmias, cardiac insufficiency, and even heart failure, all of which are the major causes of mortality and have a significant impact on the quality of life for diabetics [6,11,24]. At present, there are still no definitive diagnostic markers or preventative measures for DCM [25]. As one of the main components of Tripterygium wilfordii, Celastrol has been recently reported in some studies to prevent and treat diabetic nephropathy, insulin resistance, and obesity [26][27][28][29][30][31]. However, there is still no clarity provided on whether Celastrol has a protective effect on early energy remodeling in DCM. In addition, network pharmacology, as an emerging drug research discipline that involves cell biology, pharmacology, and systems biology, was first proposed by Chinese scholars in 2007 and then became a research hotspot in 2017. The World Federation of Chinese Medicine Societies approved and published the "Guidelines for Network Pharmacology Evaluation Methods." On the basis of what has been discussed above, a "drugtarget-disease" coexpression network was established by applying network pharmacology and taking bioinformatics approaches, so as to predict the key targets of Celastrol for the treatment of DCM, with five significant targets explored. According to the additional enrichment study of DCM through GO and KEGG, the primary signaling pathways involved in its regulation include AGE-RAGE, TNF, MAPK, TOLL-like receptor, insulin resistance, and the NODreceptor signaling pathway. Therefore, Celastrol is expected to produce a protective impact on DCM through a variety of signaling mechanisms. Both glucolipid metabolism and cardiomyocyte contractile performance can be affected by insulin resistance [32], as demonstrated by the interaction with MAPK and PI3-K signaling mechanisms. The metabolic actions of insulin are largely dependent on the role of PI3-K in regulating glucose, lipid, and protein metabolism [33,34]. As a "transmitter" in the signaling network of eukaryotic organisms, MAPK is involved in a variety of signaling pathways, including those for cell proliferation, stress, inflammation, differentiation, functional synchronization, transformation, and death [35]. As one of the most significant components of inflammatory and oxidative stress signaling pathways, MAPK phosphorylation is presumed to play a role in cell proliferation, survival, necrosis, and other pathological events [6]. Mitogen-activated protein kinase p38 (P38 MAPK), which is a critical molecule in the MAPK signaling pathway [36], plays a critical role in energy remodeling in T2DM, IR, and survival status of pancreatic β-cells. Triggered by elevated glucose, free fatty acids, and inflammatory substances, it may contribute to the mitogenic and growth-promoting activities of insulin. DCM microangiopathy, myocardial interstitial fibrosis, and myocardial hypertrophy all rely on it for development.
It has been shown in some studies that even the minimum dosage of Celastrol may significantly reduce the damage caused by diabetes-induced nephropathy. In order to exert its effects, Celastrol is involved to modify the MAPK/ NF-B signaling pathway [37]. Under the regulation of DCM, the MAPK signaling pathway plays a critical role [38,39]. At the same time, the MAPK/NF-κB signaling pathway is also crucial to the regulation of energy metabolism in DCM. Caused by abnormal glucose uptake, cardiac dysfunction is associated with the upregulation of p38 MAPK and the increase of ROS. The upregulation of ROS in diabetes can lead to the activation of p38 MAPK, which reduces the activity of insulin receptors, thus affecting the synthesis and expression of glucose transporters in cardiomyocytes through phosphatidylinositol 3. This results in myocardial mitochondrial dysfunction and the reduced efficiency of myocardial substrate production [38]. In the model rats (CL and NC groups), P38 MAPK expression was found much higher than in the HC group, indicating that P38 MAPK can be implicated in the development of DCM illness. Following the administration of Celastrol, however, P38 MAPK expression declined significantly. P38 MAPK activity was suppressed in comparison with baseline, while myocardial disruption, cell swelling, and fibrosis were alleviated, indicating the potential of Celastrol to protect against DCM by inhibiting P38 MAPK activation and acting on the insulin resistance pathway.

Conclusions
We examined the major targets and potential molecular mechanisms of Celastrol's reverse regulation of energetic remodeling of DCM from a variety of perspectives in this study and concluded that Celastrol may exert protective effects on DCM via a variety of signaling pathways. By modulating insulin resistance signaling, P38 MAPK may have a complicated regulatory function in numerous areas of energy remodeling and inflammation in DCM. This gives * *

Limitations
The limitations of this study include the small sample size and the lack of experimental studies on activation and inhibition at the cellular level for the specific mechanism of Celastrol's reverse regulation of early energy remodeling in DCM.

Data Availability
The data used for the study are included within the article and the supplementary files.